1. Field of the Invention
The present invention relates to an image-processing apparatus which has an image region distinction processing capability to perform an image processing according to a type of image data, and an image region distinction processing method.
2. Description of the Related Art
In general, in an image processing apparatus, for example, in a digital copier, various methods are used in order to improve picture quality when an image signal read from an original document by an image sensor is printed and outputted to a recording sheet. As one method of improving the picture quality, a character region, a dot region and the like contained in information described on an original document are respectively classified, and an image processing corresponding to the characteristic of an image of each of the regions is performed to realize high-quality print output. In this image processing, for example, with respect to the dot region, such as a photograph, in the information classified on the original document, a smoothening processing is performed in order to suppress a moire, and with respect to the character region, an emphasis processing is performed in order to emphasize the contour of a character. At this time, when a region distinction for classification based on each image type is erroneously made, the smoothening processing is performed on the character region, and the contour emphasis processing is performed on the dot region, and accordingly, the opposite effect occurs. Accordingly, the image region distinction has a very important role in order to improve the picture quality.
As an image region distinction method, for example, JP-A-10-112800 proposes a method of distinguishing a dot region in a mixed image of characters, dots and the like. A density difference (edge feature amount) between a marked pixel and an adjacent pixel is calculated for each marked pixel, and it is primarily determined from the density difference whether the density of the marked pixel is a peak value or not. In addition, the number of peak values in region pixels is calculated, and in the case where at least one peak value exists, the region is made a dot candidate. Next, the number of similar dot candidates of peak values existing in a specified number of pixels is calculated. It is determined whether the ratio of the dot candidates existing in the previously determined number of pixels is 90 percent or more. Further, the continuity of the dot region is determined, a discrimination is made between dot detection of 100 lines or less close to a character and thin dot detection of 100 lines or more, and an image reproduction processing according to the fineness of the dot part is performed.
As stated above, according to whether the number of pixels having the density difference exceeds a previously determined threshold value or not, a distinction is made between a character and a non-character (photograph, picture pattern, etc.). However, in an actual distinction, an obtained image signal is different from a true image signal by various factors, such as reading performance of a scanner and disturbance such as vibration, and accordingly, a complete image region distinction is very difficult, an accurate distinction can not be made, and an erroneous discrimination occurs between the character region and the dot region. Besides, in a general region distinction processing, although a distinction is made based on a previously set fixed threshold value (parameter), it is difficult to perform a high-precision distinction processing on images of various forms.